Publications
List and links to my PhD dissertation, papers and talks
Articles
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Automated Spatio-Temporal Weather Modeling for Load Forecasting, Julie Keisler and Margaux Brégère, International Ruhr Energy Conference, 2024, Best paper award
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MetaCURL: Non-stationary Concave Utility Reinforcement Learning, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, NeurIPS, 2024
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(Online) Convex Optimization for Demand-Side Management: Application to Thermostatically Controlled Loads, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, Submitted, 2024
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A bandit approach with evolutionary operators for model selection: Application to neural architecture optimization for image classification, Margaux Brégère and Julie Keisler, Submitted, 2024
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Automated Deep Learning for load forecasting, Julie Keisler, Sandra Claudel, Gilles Cabriel, Margaux Brégère, AUTOML (International Conference on Automated Machine Learning), 2024
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Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, AISTATS (The 21st International Conference on Artificial Intelligence and Statistics), 2024
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Online Hierarchical Forecasting for Power Consumption Data, Margaux Brégère and Malo Huard, International Journal of Forecasting, 2022, IIF-Tao Hong Award
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Simulating tariff impact in electrical energy consumption profiles with conditional variational autoencoders, Margaux Brégère and Ricardo J. Bessa, IEEE Access, 2020
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Target Tracking for Contextual Bandits : Application to Demand Side Management, Margaux Brégère, Pierre Gaillard, Yannig Goude and Gilles Stoltz, ICML (International Conference on Machine Learning), pages 754–763, 2019
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A variable selection approach in the multivariate linear model : An application to LC-MS metabolomics data, Marie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet, Laure Sansonnet, Margaux Brégère, Marie-Pierre Etienne, Stéphane Robin and Grégory Genta-Jouve, Statistical Applications in Genetics and Molecular Biology, vol. 17, n. 5, 2018
PhD
- Stochastic Bandit Algorithms for Demand Side Management, University of Paris Saclay (Laboratoire de Mathématiques d’Orsay, EDF R&D, Inria Paris), under the supervision of Gilles Stoltz, Yannig Goude and Pierre Gaillard, 2020, ThinkSmartGrids 2022 awards - AMIES 2021 award
Talks
- Meetup Paris Women in Machine Learning & Data Science, Critéo AI Lab, Paris, France, April 2024
- Séminaire Parisien de Statistique, Institut Henri-Poincaré, Paris, France, April 2024
- WPI-Workshop on Stochastics, Statistics, Machine Learning and their Applications of Sustainable Finance and Energy Markets, Wolfgang-Pauli Institute Vienna, Austria, September 2023
- IIF Workshop on Forecast Reconciliation, Monash University, Prato, Italy, September 2023
- Women in Data Science Conference, online, April 2023
- New Year’s address of the ThinkSmartGrids association, online, January 2022
- Phiméca workshop, Henri Poincaré Institut, Paris November 2021
- FrENBIS conference, online, September 2021
- PhD defense, online, December 2020
- Lab Meeting of Center for Power and Energy Systems, online, November 2020
- IA Summer School of BNP, Campus BNP Paribas, Louveciennes, August 2019
- International Conference on Machine Learning, Long Beach, USA, June 2019
- Statistics Days, Nancy, June 2019
- 8th Young Statisticians Meeting, Porquerolles, April 2019
- Machine Learning in Real Word, Critéo Lab, Paris, October 2019
- Workshop on energy transition WTE 2018, EDF Lab, Palaiseau, November 2018
- Junior Conference on Data Science and Engineering, Orsay, September 2017
Others
- Interview for docteurs SPI, August 2022
- Feedback on CIFRE PhD, City of Sciences, Paris, October 2019 and 2020